scispace - formally typeset
Search or ask a question
Author

Rajagopalan Sridharan

Bio: Rajagopalan Sridharan is an academic researcher from National Institute of Technology Calicut. The author has contributed to research in topics: Flexible manufacturing system & Flow shop scheduling. The author has an hindex of 16, co-authored 57 publications receiving 717 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: In this paper, an ACO based meta-heuristic is developed for solving both small scale and large scale problem instances in a reasonable amount of time for solving large scale instances, the performance of the proposed ACO-based meta heuristic is improved by integrating it with a variable neighbourhood search.
Abstract: The traditional distribution planning problem in a supply chain has often been studied mainly with a focus on economic benefits. The growing concern about the effects of anthropogenic pollutions has forced researchers and supply chain practitioners to address the socio-environmental concerns. This research study focuses on incorporating the environmental impact on route design problem. In this work, the aim is to integrate both the objectives, namely economic cost and emission cost reduction for a capacitated multi-depot green vehicle routing problem. The proposed models are a significant contribution to the field of research in green vehicle routing problem at the operational level. The formulated integer linear programming model is solved for a set of small scale instances using LINGO solver. A computationally efficient Ant Colony Optimization (ACO) based meta-heuristic is developed for solving both small scale and large scale problem instances in reasonable amount of time. For solving large scale instances, the performance of the proposed ACO based meta-heuristic is improved by integrating it with a variable neighbourhood search.

82 citations

Journal ArticleDOI
TL;DR: The results indicate that setup-oriented rules provide better performance than ordinary rules and the difference in performance increases with the increase in shop load and setup time ratio.
Abstract: This paper presents the salient aspects of a simulation-based experimental study of scheduling rules for scheduling a dynamic job shop in which the setup times are sequence-dependent. A discrete event simulation model of the job shop system is developed for the purpose of experimentation. Seven scheduling rules from the literature are incorporated in the simulation model. Five new setup-oriented scheduling rules are proposed and implemented. Simulation experiments were conducted under various experimental conditions characterized by factors such as shop load, setup time ratios, and due date tightness. The results indicate that setup-oriented rules provide better performance than ordinary rules. The difference in performance between these two groups of rules increases with the increase in shop load and setup time ratio. One of the proposed rules performs better for mean flow time and mean tardiness measures.

67 citations

Journal ArticleDOI
TL;DR: In this paper, a simulation study was carried out for analyzing the impact of scheduling rules that control part launching and tool request selection decisions of a flexible manufacturing system (FMS) operating under tool movement along with part movement policy.
Abstract: This paper presents the details of a simulation study carried out for analyzing the impact of scheduling rules that control part launching and tool request selection decisions of a flexible manufacturing system (FMS) operating under tool movement along with part movement policy. Two different scenarios have been investigated with respect to the operation of FMS. In scenario 1, the facilities such as machines, tool transporter and part transporter are assumed to be continuously available without breakdowns, whereas in scenario 2, these facilities are prone to failures. For each of these scenarios, a discrete-event simulation model is developed for the purpose of experimentation. A number of scheduling rules are incorporated in the simulation models for the part launching and tool request selection decisions. The performance measures evaluated are mean flow time, mean tardiness, mean waiting time for tool and percentage of tardy parts. The results obtained through the simulation have been statistically analyzed. The best possible scheduling rule combinations for part launching and tool request selection have been identified for the chosen FMS.

58 citations

Journal ArticleDOI
TL;DR: In this article, a mixed integer linear programming model with a profit maximization objective is proposed to design a multi-stage reverse logistics network for product recovery, where different recovery options such as product remanufacturing, component repairing and material recycling are simultaneously considered.

54 citations

Journal ArticleDOI
TL;DR: A simulation-based experimental study of scheduling rules for scheduling a dynamic job shop in which the setup times are sequence-dependent indicates that setup-oriented rules provide better performance than ordinary rules.
Abstract: This paper presents the salient aspects of a simulation-based experimental study of scheduling rules for scheduling a dynamic job shop in which the setup times are sequence-dependent. A discrete-event simulation model of the job shop system is developed for the purpose of experimentation. Seven scheduling rules from the literature are incorporated in the simulation model. Five new setup-oriented scheduling rules are proposed and implemented. Simulation experiments have been conducted under experimental conditions characterised by different setup time ratios. The simulation results are analysed using statistical significance tests. The results indicate that setup-oriented rules provide better performance than ordinary rules. The difference in performance between these two groups of rules increases with increase in shop load and setup time ratio. One of the proposed rules performs better for mean flow time and mean tardiness measures. Multiple linear regression based metamodels have been developed for the b...

53 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: The aim of this paper is to review recently published papers in reverse logistic and closed-loop supply chain in scientific journals and identify gaps in the literature to clarify and to suggest future research opportunities.

1,364 citations

Journal ArticleDOI
TL;DR: A comprehensive review of discrete event simulation publications published between 2002 and 2013 with a particular focus on applications in manufacturing is provided in this paper, where the literature is classified into three general classes of manufacturing system design, manufacturing system operation, and simulation language/package development.

448 citations

Journal ArticleDOI
Ali Allahverdi1
TL;DR: This paper is the third comprehensive survey paper which provides an extensive review of about 500 papers that have appeared since the mid-2006 to the end of 2014, including static, dynamic, deterministic, and stochastic environments, based on shop environments as single machine, parallel machine, flowshop, job shop, or open shop.

369 citations

Journal ArticleDOI
TL;DR: This paper explores the future research direction in SDS and discusses the new techniques for developing future new JSP scheduling models and constructing a framework on solving the JSP problem under Industry 4.0.
Abstract: Traditional job shop scheduling is concentrated on centralized scheduling or semi-distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and distributed manufacturing system supported by novel and emerging manufacturing technologies such as mass customization, Cyber-Physics Systems, Digital Twin, and SMAC (Social, Mobile, Analytics, Cloud). The scheduling research needs to shift its focus to smart distributed scheduling modeling and optimization. In order to transferring traditional scheduling into smart distributed scheduling (SDS), we aim to answer two questions: (1) what traditional scheduling methods and techniques can be combined and reused in SDS and (2) what are new methods and techniques required for SDS. In this paper, we first review existing researches from over 120 papers and answer the first question and then we explore a future research direction in SDS and discuss the new techniques for developing future new JSP scheduling models and constructing a framework on solving the JSP problem under Industry 4.0.

308 citations

Journal ArticleDOI
TL;DR: A novel multi-objective multi-period mixed integer program for reverse logistics network design in epidemic outbreaks, which aims at determining the best locations of temporary facilities and the transportation strategies for effective management of the exponentially increased medical waste within a very short period is proposed.
Abstract: The outbreak of an epidemic disease may pose significant treats to human beings and may further lead to a global crisis. In order to control the spread of an epidemic, the effective management of rapidly increased medical waste through establishing a temporary reverse logistics system is of vital importance. However, no research has been conducted with the focus on the design of an epidemic reverse logistics network for dealing with medical waste during epidemic outbreaks, which, if improperly treated, may accelerate disease spread and pose a significant risk for both medical staffs and patients. Therefore, this paper proposes a novel multi-objective multi-period mixed integer program for reverse logistics network design in epidemic outbreaks, which aims at determining the best locations of temporary facilities and the transportation strategies for effective management of the exponentially increased medical waste within a very short period. The application of the model is illustrated with a case study based on the outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China. Even though the uncertainty of the future COVID-19 spread tendency is very high at the time of this research, several general policy recommendations can still be obtained based on computational experiments and quantitative analyses. Among other insights, the results suggest installing temporary incinerators may be an effective solution for managing the tremendous increase of medical waste during the COVID-19 outbreak in Wuhan, but the location selection of these temporary incinerators is of significant importance. Due to the limitation on available data and knowledge at present stage, more real-world information are needed to assess the effectiveness of the current solution.

238 citations